DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Google Cloud Datastore vs. NSDb vs. Riak TS vs. Titan

System Properties Comparison Google Cloud Datastore vs. NSDb vs. Riak TS vs. Titan

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonNSDb  Xexclude from comparisonRiak TS  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelDocument storeTime Series DBMSTime Series DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score0.28
Rank#307  Overall
#27  Time Series DBMS
Websitecloud.google.com/­datastorensdb.iogithub.com/­thinkaurelius/­titan
Technical documentationcloud.google.com/­datastore/­docsnsdb.io/­Architecturewww.tiot.jp/­riak-docs/­riak/­ts/­latestgithub.com/­thinkaurelius/­titan/­wiki
DeveloperGoogleOpen Source, formerly Basho TechnologiesAurelius, owned by DataStax
Initial release2008201720152012
Current release3.0.0, September 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open SourceOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ScalaErlangJava
Server operating systemshostedLinux
macOS
Linux
OS X
Linux
OS X
Unix
Windows
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyes: int, bigint, decimal, stringnoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesyesall fields are automatically indexedrestrictedyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query languageyes, limitedno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC
HTTP REST
WebSocket
HTTP API
Native Erlang Interface
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Clojure
Java
Python
Server-side scripts infoStored proceduresusing Google App EnginenoErlangyes
TriggersCallbacks using the Google Apps Engineyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyesyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono infolinks between datasets can be storedyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noUser authentification and security via Rexster Graph Server

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Google Cloud DatastoreNSDbRiak TSTitan
DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

show all

Recent citations in the news

Best cloud storage of 2024
4 June 2024, TechRadar

Google Cloud Stops Exit Fees
12 January 2024, Spiceworks News and Insights

Inside Google’s strategic move to eliminate customer cloud data transfer fees
12 January 2024, Network World

BigID Data Intelligence Platform Now Available on Google Cloud Marketplace
6 November 2023, PR Newswire

Google says it'll stop charging fees to transfer data out of Google Cloud
11 January 2024, TechCrunch

provided by Google News

New Basho Data Platform Provides Operational Simplicity for Enterprise Big Data Applications
7 June 2015, insideBIGDATA

provided by Google News

Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database | Amazon Web Services
24 August 2015, AWS Blog

Titan Graph Database Integration with DynamoDB: World-class Performance, Availability, and Scale for New Workloads
20 August 2015, All Things Distributed

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

DataStax acquires Aurelius, the startup behind the Titan graph database
3 February 2015, VentureBeat

DSE Graph review: Graph database does double duty
14 November 2019, InfoWorld

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here